The ASM Science Journal publishes advancements in the broad fields of medical, engineering, earth, mathematical, physical, chemical and agricultural sciences as well as ICT. Scientific articles published will be on the basis of originality, importance and significant contribution to science, scientific research and the public.     Scientific articles published will be on the basis of originality, importance and significant contribution to science, scientific research and the public. Scientists who subscribe to the fields listed above will be the source of papers to the journal. All articles will be reviewed by at least two experts in that particular field.

The ASM Science Journal publishes the latest research advancements in the fields of medical, engineering, earth, mathematical, physical, chemical, and agricultural sciences, as well as information and communication technology (ICT). All published scientific articles must demonstrate originality, significance, and a substantial contribution to science, scientific research, and the public. The papers submitted to the journal are sourced from scientists in the aforementioned fields, and all articles will be reviewed by at least two experts in the respective field.

ASM科学期刊发表医学、工程、地球、数学、物理、化学和农业科学以及信息与通信技术（ICT）领域的最新研究进展。所有发表的科学文章必须具备原创性、重要性和对科学、科研及公众的显著贡献。该期刊的论文来源于上述领域的科学家，所有文章将由至少两位该领域的专家进行审稿。

ASM Science Journal

Thottea grandiflora is a plant commonly called “Hempedu Beruang” and is widely distributed in Peninsular Malaysia. T. grandiflora plant’s part is used in folk medicine for health benefits such as fever, asthma, cough, diabetes, malaria, stomach disorder, back pain, and lung tumours. This plant has reported pharmacological activities like antidiabetic, anti-inflammatory, antimicrobial, antifungal, and antihyperglycemic. However, this plant is not much explored despite many traditional claims by the local tribes on the potential use of the plant. This study aimed to review the botanical characterisation, traditional uses, phytochemical constituents and pharmacological actions of T. grandiflora. This review is based on published electronic database literature on the traditional uses, pharmacology, and chemistry of T. grandiflora. The electronic databases used were Google Scholar, Science Direct, PubMed and Scopus. The plant parts can be further analysed for their clinical effects and utilised in pharmaceutical product development.

Vikneswari Perumal

Tavamani Balan

Nurul Fateha Muhamad Nizam

Laavanya Rajendhiran

Nur Ainina Hani Ghazali

Suganya Murugesu

Sharon Fatinathan

Thottea grandiflora: A Review on its Traditional Uses, Phytochemical Constituents and Pharmacological Actions

大花假番荔枝：关于其传统用途、植物化学成分及药理作用的综述

This study explores the application of artificial intelligence (AI) technology in promoting inclusive learning in underserved schools. By integrating personalised learning platforms, intelligent tutoring systems, and automated management tools, this research evaluates the impact of AI on academic performance, learning engagement, and teacher workload. The experimental results show that AI-driven personalised learning paths and real-time feedback mechanisms significantly improved student learning outcomes, particularly in subjects such as mathematics and science. In addition, teachers' administrative burdens were effectively reduced through automated tools. The study also analyses challenges such as insufficient infrastructure and data privacy protection, proposing targeted technical solutions. This paper provides practical guidance for policymakers and educational institutions to promote the implementation of AI technology in low-resource environments.

Wai Yie Leong

Transforming Rural and Underserved Schools with AI-Powered Education Solutions

用人工智能教育解决方案改造农村和欠服务学校

University rankings play a crucial role in the higher education landscape, shaping perceptions of academic quality, research productivity, and institutional reputation. This paper provides a comprehensive technical analysis of university ranking methodologies, examining the metrics, methods, and implications of various ranking systems. We explore the diverse approaches used by ranking organisations, the strengths and limitations of different methodologies, and the impact of rankings on higher education institutions and stakeholders. By critically evaluating ranking methodologies and discussing emerging trends and challenges, this paper aims to provide insights into the complex landscape of university rankings and inform discussions on their relevance and utility in the global higher education community.

Zhang Jing Bing

Revolution in University Ranking System

大学排名体系的革命

In contemporary times, the utilisation of social networks entails inherent risks, particularly on platforms such as Instagram, Twitter, and TikTok, which facilitate anonymous usage and the creation of fictitious profiles. The cloak of anonymity has fostered an ideal environment for cyberbullying, a form of harassment that unfolds in the virtual realm accessed by children and youth through information and communication technologies like the Internet and cell phones. Cyberbullying is pervasive across numerous countries globally. Consequently, a multitude of studies have delved into diverse solutions aimed at preventing cyberbullying, including various approaches and techniques for identifying and detecting it through the analysis of text language. This systematic review seeks to encompass these scientific studies that primarily focus on the classification of cyberbullying based on the language employed in online communication.

Zineb Lamghari

Popular Cyberbullying Detection Methods on Social Media

社交媒体上的网络欺凌检测方法研究

Plastic bags consist of synthetic organic polymers that are produced for one-time usage to carry things around. They are lightweight, cheap for mass production and often distributed at no cost in places such as supermarket and shopping malls. There might be numerous factors that affect this increasing usage of plastic bags among the public. The overall objective of this study was to identify factors that influence plastic bag consumption among Malaysians using the Theory of Planned Behaviour. Data were collected by distributing an online questionnaire to the local community. Non-probability purposive sampling method was adopted to select the three states in Malaysia. The path analysis was performed to investigate the relationship between predictor factors (i.e., attitude, subjective norms, perceived behavioural control and intention) and minimal plastic bag usage. A total of 386 people from different ages and backgrounds in Malaysia participated in the research. The findings showed that an individual’s attitude (β = 0.331) and perceived behaviour (β = 0.414) significantly influenced the intention to use plastic bags. The perceived behavioural control (β = 0.329) and intention (β = 0.486) have also significantly influenced the behaviour to minimise plastic bag usage. However, subjective norms did not significantly influence the intention (β = 0.060). This study showed that perceived behavioural control and intention are important predictors towards minimal usage of plastic bags. Therefore, it is recommended to enhance education and awareness programmes among the public in order to change the attitude, perceived behavioural control and intention towards minimal usage of plastic bags. High generation and mismanagement of plastic bag waste, which may lead to a negative impact on environmental health, are the main issues that should be addressed properly by the Malaysian population.

Jeffery Stephen

Predicting Minimal Usage of Plastic Bags Behaviour among Malaysian Adults

预测马来西亚成年人最低限度使用塑料袋行为

Process mining empowers companies to optimise operational processes by deriving insights from event logs. It involves assessing event logs or the resultant process models against existing models and identifying challenges within executed processes to enhance their efficiency. However, a critical prerequisite for effective process mining is data cleaning, which simplifies the complexities inherent in real-world event data, making it amenable to comprehension, processing, and leveraging with process mining techniques. Consequently, new methodologies and approaches for event data pre-processing have garnered significant attention within the business process scientific community. This paper presents a systematic literature review summarising relevant techniques for event data pre-processing in the context of business process mining. The objective of this study is to categorise approaches and methodologies related to event data pre-processing while shedding light on the crucial issues associated with these techniques.

Exploring Event Data Pre-processing Approaches for Business Process Mining

探索业务流程挖掘中的事件数据预处理方法

Coronavirus disease (COVID-19) is an extremely transmissible disease that causes tremendous human suffering worldwide, with millions of people dying within two years. In Malaysia, the COVID-19 pandemic continues with an increasing number of positive cases. In order to monitor and prevent the disease, disease mapping is proposed for quantifying and describing the disease risk. The primary objective of this research is to estimate the COVID-19 relative risk using one of the most widely employed Bayesian approaches, namely the Poisson-gamma model, and eventually display a disease map to show the COVID-19 risk level in each state. The relative risk results are divided into five different levels to classify the COVID-19 risk level in each Malaysian state. The illustration of five different shades in the disease mapping has distinguished the risk levels within each state, where the most light-coloured area indicates very low risk whilst the most dark-coloured area indicates very high risk. According to the results, the area with the lowest risk of contracting COVID-19 in 2020 is Perlis, and the area with the highest risk is Labuan, whereas in 2021, Perlis remains the lowest risk area while Selangor is the highest risk area.

Nazrina Aziz

COVID-19 Disease Mapping in Malaysia Using Poisson-gamma Model to Safeguard Community

使用泊松-伽马模型保护社区的马来西亚新冠病毒疾病地图

According to 2019 statistics in Indonesia, the number of motorcycle accidents is relatively high, at 84.4 percent. Other data show that 16.13 percent of accidents include drivers who have previously been in an accident. The purpose of this study is to obtain a model of the probability of an accident for motorcycle riders who have previously experienced an accident as well as for motorcycle riders who have never experienced an accident before. Data were collected by interviewing motorcycle riders who had only been in one traffic accident and those who had been in more than one. The results of the analysis suggest that a driver who has had a previous accident has a 16 percent probability of having an accident, but a driver who has never had an accident has an 84 percent probability of having an accident. Furthermore, validation is carried out by calculating the Mean Absolute Deviation (MAD) value. The MAD value calculated from the results is 11.16 percent. Following that, numerous scenarios were run, with scenario 1 demonstrating that female drivers who have previously been in an accident have a higher accident probability than male drivers who have previously been in an accident. Meanwhile, scenario 2 shows that drivers above the age of 20 who have had a previous accident are more likely to be involved in an accident than drivers under the age of 20. Scenario 3 reveals that drivers who are on varied roadside variable roads and driving on bends can reduce their monotone level from 45% to 22%, but this condition has no effect on the level of fatigue and the probability of accidents. The final scenario shows that a driver who drives between 24:00 and 06:00 will have probability of fatigue by 73% and will have accident probability by 17%. Finding of this study is the drivers who have previously been involved in an accident are less likely to be involved in another accident compared to the drivers who have never been involved in an accident before.

Pada Lumba

Farouk Sumarli

The Impact of Previous Accidents on The Probability of Repeat Accidents to Motorcyclists

先前事故对摩托车骑手重复事故概率的影响

This research investigates the structural behaviour of stainless-steel beams (SSBs) when subjected to extreme temperatures, specifically in the context of fire-induced deformations. High temperatures, typical of fire occurrences, exert large thermal loads on SSBs, leading in material property changes that make the metal more brittle, stiffer, and brittle. The objective of this study is to investigate extensively the behaviour of SSBs under the combined impact of heat transfer and applied loads, with a focus on substantial deflections. To completely assess the performance of SSBs, we undertake parametric investigations and systematic research efforts. The initial phase comprises a thorough review of relevant data about the behaviour of SSBs at increased temperatures. Afterwards, a parametric study of the web section is conducted to determine the performance of the SSBs under exposure to fire and applied stresses. In order to ease the numerical research, the finite element (FE) program ABAQUS CAE is used to simulate stainless steel I-section beams of varying diameters subjected to realistic fire conditions according to the ISO 834 standard fire curve. The average discrepancy between numerical forecasts and experimental data for six separate models about the final temperature readings is 2.74 percent. Prior to actual collapse, the axial displacement of the SSBs decreases by around 7.5%, showing significant temperature influences on their strength. In addition, the axial deformation of the SSBs exhibits greater displacements in the web portion than in the flange section following fire exposure and loading. This discovery highlights the need to take into account the unique thermal expansion and stiffness characteristics of the web and flange components during fire occurrences. Utilising the finite element approach in ABAQUS reveals the resistance of SSBs to increased temperatures. The findings highlight the potential advantages of using stronger SSBs to maximise the structural response under fire conditions. This study gives useful insights into the thermal behaviour of SSBs and has important implications for building fire-resistant structures, boosting the fire safety of constructions, and enhancing their resistance against fire risks.

ISSN	1823-6782
h-index	11

Publication Information	Publisher: Akademi Sains Malaysia，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2017，Proportion of original research papers: 0.00%，Self Citation Rate:N.A.， Gold OA Rate: 0.00%
Average review cycle	24 weeks

ASM Science Journal

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Thottea grandiflora: A Review on its Traditional Uses, Phytochemical Constituents and Pharmacological Actions

Transforming Rural and Underserved Schools with AI-Powered Education Solutions

Revolution in University Ranking System

Popular Cyberbullying Detection Methods on Social Media

Predicting Minimal Usage of Plastic Bags Behaviour among Malaysian Adults

Exploring Event Data Pre-processing Approaches for Business Process Mining

COVID-19 Disease Mapping in Malaysia Using Poisson-gamma Model to Safeguard Community

Predicting Minimal Usage of Plastic Bags Behaviour among Malaysian Adults

The Impact of Previous Accidents on The Probability of Repeat Accidents to Motorcyclists

Mechanical Response and Failure Analysis of Stainless-Steel Beams Exposed to Elevated Temperatures